This section is intended to introduce the reader to various aspects of art, which may be related to various aspects of the present invention that are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present invention. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
Modem computer databases may store immense amounts of data in databases or the like. This data may hold valuable information that is essentially unusable in its raw form because of the sheer magnitude of the information. However, valuable information may become apparent if the data is properly presented. For example, extraction of such information may be facilitated by presenting the data in a form that allows users to readily observe correlations between data points. Accordingly, many business researchers and data analysts, for example, have long sought to transform large amounts of raw data into valuable business and research intelligence by properly arranging and displaying the data for evaluation. One means of achieving the transformation of raw data into valuable information may include the conversion of the raw numerical data into visual data, which allows users to analyze graphic displays through pattern and trend recognition.
Typically, users construct traditional bar charts, line charts, and flow charts from raw data to provide means for viewing the data in a form conducive to some level of analysis. However, the usefulness of these traditional charts may be limited because of their inability to display large amounts of information in a meaningful format. In many cases, too many graphic features may overwhelm users. Also, users are often unable to perform a proper analysis because of an inability to easily access relevant associated data. For example, the traditional charts mentioned above often force users to navigate through many different charts, reports, and diagrams in order to acquire information needed to make informed decisions. Accordingly, with these traditional charts, users are less able to recognize trends and common patterns, often preventing users from understanding underlying data and observing “cause and effect” paths. Additionally, traditional visualization tools may not assist in identification of key patterns, trends, and relationships and, do not allow users to easily delve deeper into the data.